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Modellers of biological, ecological, and environmental systems cannot take for granted the maxim 'simple means general means good'. We argue here that viewing simple models as the main way to achieve generality may be an obstacle to the progress of ecological research. We show how complex models can be both desirable and general, and how simple and complex(More)
What are the origins of the epistemological difficulties concerning representation? How have philosophers of science studying models and representation reacted to these difficulties? How else might scientific models be approached if not representationally? In addressing such questions, Models as Epistemic Artefacts: Toward a Non-Representationalist Account(More)
We develop a framework for discussing the degree of conceptual autonomy of natural and artificial agents. We claim that aspects related to learning and communication necessitate adaptive agents that are partially autonomous. We demonstrate how partial conceptual autonomy can be obtained through a self-organization process. The input for the agents consists(More)
In this article we approach neural networks as computational templates that travel across various sciences. Traditionally, it has been thought that models are primarily models of some target systems: they are assumed to represent partially or completely their target systems. We argue, instead, that many computational models cannot easily be conceived of in(More)
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